Subjective testing plays an important role in the research field of audio technologies. According to industry standards (for example, International Telecommunications Union-Telecommunications Standardization Sector (ITU-T) P.800), several testers are organized to listen to and test a series of audio sequences, and then statistics on an average trend of quality graded by the testers are collected, which are generally represented by Mean Opinion Score (MOS). A score reflects quality of related audio technology.
However, subjective testing has disadvantages of a long experimental period and high economic costs; and it is impractical to organize subjective tests in large quantities in a middle phase of an audio algorithm research. Therefore, it has a significant meaning to study an objective testing tool. From the perspective of methodology, by using methods such as mathematics and signal processing, an objective testing tool abstracts a scoring system and outputs a quality evaluation result, and correspondingly, an output is represented by MOS-Listening Quality Objective (MOS-LQO).
Up to now, many objective evaluation tools have emerged in the industry. Objective quality evaluation tools may be simply classified into two categories: intrusive and non-intrusive. Generally, in an existing network, a reference signal is hard to obtain due to various constraints. Therefore, a non-intrusive model is increasingly demanded and is more technically challenging.
A modeling method of the non-intrusive signal domain model ITU-T P.563 in the prior art is based on an oral phonation mechanism, but a so-called voice quality evaluation is a perception process of an auditory system, which sharply differs from the foregoing oral phonation mechanism. In addition, the oral phonation mechanism generally involves a large quantity of assumptions and simplification, and there is inaccuracy in a universal application. Therefore, accuracy of a voice quality evaluation determined by using the non-intrusive signal domain model is not high.